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| author | AUTOMATIC1111 <16777216c@gmail.com> | 2023-07-18 18:20:22 +0300 |
|---|---|---|
| committer | AUTOMATIC1111 <16777216c@gmail.com> | 2023-07-18 18:20:22 +0300 |
| commit | eb7c9b58fc2fbab205d4bc9f708800870dcda3fb (patch) | |
| tree | 337bc9e4e6793aa072c2e2a8c10e3a3f7daf6a95 /extensions-builtin/Lora/network_lokr.py | |
| parent | f865d3e11647dfd6c7b2cdf90dde24680e58acd8 (diff) | |
| parent | 7f7db1700bda40ba3171a49b6a4ef38f868b7d0a (diff) | |
Merge branch 'dev' into release_candidate
Diffstat (limited to 'extensions-builtin/Lora/network_lokr.py')
| -rw-r--r-- | extensions-builtin/Lora/network_lokr.py | 64 |
1 files changed, 64 insertions, 0 deletions
diff --git a/extensions-builtin/Lora/network_lokr.py b/extensions-builtin/Lora/network_lokr.py new file mode 100644 index 00000000..340acdab --- /dev/null +++ b/extensions-builtin/Lora/network_lokr.py @@ -0,0 +1,64 @@ +import torch
+
+import lyco_helpers
+import network
+
+
+class ModuleTypeLokr(network.ModuleType):
+ def create_module(self, net: network.Network, weights: network.NetworkWeights):
+ has_1 = "lokr_w1" in weights.w or ("lokr_w1_a" in weights.w and "lokr_w1_b" in weights.w)
+ has_2 = "lokr_w2" in weights.w or ("lokr_w2_a" in weights.w and "lokr_w2_b" in weights.w)
+ if has_1 and has_2:
+ return NetworkModuleLokr(net, weights)
+
+ return None
+
+
+def make_kron(orig_shape, w1, w2):
+ if len(w2.shape) == 4:
+ w1 = w1.unsqueeze(2).unsqueeze(2)
+ w2 = w2.contiguous()
+ return torch.kron(w1, w2).reshape(orig_shape)
+
+
+class NetworkModuleLokr(network.NetworkModule):
+ def __init__(self, net: network.Network, weights: network.NetworkWeights):
+ super().__init__(net, weights)
+
+ self.w1 = weights.w.get("lokr_w1")
+ self.w1a = weights.w.get("lokr_w1_a")
+ self.w1b = weights.w.get("lokr_w1_b")
+ self.dim = self.w1b.shape[0] if self.w1b is not None else self.dim
+ self.w2 = weights.w.get("lokr_w2")
+ self.w2a = weights.w.get("lokr_w2_a")
+ self.w2b = weights.w.get("lokr_w2_b")
+ self.dim = self.w2b.shape[0] if self.w2b is not None else self.dim
+ self.t2 = weights.w.get("lokr_t2")
+
+ def calc_updown(self, orig_weight):
+ if self.w1 is not None:
+ w1 = self.w1.to(orig_weight.device, dtype=orig_weight.dtype)
+ else:
+ w1a = self.w1a.to(orig_weight.device, dtype=orig_weight.dtype)
+ w1b = self.w1b.to(orig_weight.device, dtype=orig_weight.dtype)
+ w1 = w1a @ w1b
+
+ if self.w2 is not None:
+ w2 = self.w2.to(orig_weight.device, dtype=orig_weight.dtype)
+ elif self.t2 is None:
+ w2a = self.w2a.to(orig_weight.device, dtype=orig_weight.dtype)
+ w2b = self.w2b.to(orig_weight.device, dtype=orig_weight.dtype)
+ w2 = w2a @ w2b
+ else:
+ t2 = self.t2.to(orig_weight.device, dtype=orig_weight.dtype)
+ w2a = self.w2a.to(orig_weight.device, dtype=orig_weight.dtype)
+ w2b = self.w2b.to(orig_weight.device, dtype=orig_weight.dtype)
+ w2 = lyco_helpers.make_weight_cp(t2, w2a, w2b)
+
+ output_shape = [w1.size(0) * w2.size(0), w1.size(1) * w2.size(1)]
+ if len(orig_weight.shape) == 4:
+ output_shape = orig_weight.shape
+
+ updown = make_kron(output_shape, w1, w2)
+
+ return self.finalize_updown(updown, orig_weight, output_shape)
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